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Life sciences · Journal article
International Journal of Nanomedicine · October 31, 2026
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Abstract: Metal–organic frameworks (MOFs) can coordinate copper, catalytic sites and therapeutic cargo within one carrier, offering opportunities to control copper exposure and cellular susceptibility. Establishing their contribution to cuproptosis requires evidence connecting these design functions to copper delivery and the cell-death mechanism. This critical narrative review proposes "executable cuproptosis” as a delivery and evaluation framework for examining that connection. We assess selected MOF platforms across mechanistic validation, mitochondrial access, tumor context and translational requirements, with comparisons to other copper-delivery approaches. The reviewed examples show that material design can influence copper release, retention and treatment responses, while evidence linking these effects to mitochondrial copper and cuproptosis-specific causality remains uneven. Copper accumulation, carrier colocalization, oxidative stress and tumor inhibition support different claims; their interpretation depends on the measurement and functional controls. Combination studies require quantitative assessment of interaction and separate validation of each claimed death pathway or immune effect. Pharmacokinetic, biodistribution and long-term safety data remain incomplete, especially for organic linkers and transformation products, and the candidate biomarkers discussed here lack validation for clinical selection in MOF-enabled cuproptosis therapy. We identify priorities in mitochondrial copper measurement, tumor heterogeneity, component disposition and manufacturing reproducibility. The evidence remains predominantly preclinical. The framework organizes further development around testable links between delivery, mechanism and tumor state; its predictive value and the clinical benefit of MOF-enabled cuproptosis remain to be established. Keywords: cuproptosis, metal-organic frameworks, nanomedicine, copper delivery, mitochondria, biomarkers, translational filters